Investigation of New Unsupervised Processing Methods for P300-Based Brain-Computer Interface
نویسندگان
چکیده
منابع مشابه
Control of a 2-DoF robotic arm using a P300-based brain-computer interface
In this study, a novel control algorithm, based on a P300-based brain-computer interface (BCI) is fully developed to control a 2-DoF robotic arm. Eight subjects including 5 men and 3 women perform a 2-dimensional target tracking in a simulated environment. Their EEG (Electroencephalography) signals from visual cortex are recorded and P300 components are extracted and evaluated to perform a real...
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The goal of this work was to describe a system for real-time typing controlled by brain biopotential signals. A 6 ( 6 matrix containing Russian alphabet letters and auxiliary symbols was shown on PC screen. Electroencephalogram was taken, and the P300 component was extracted (this component appeared only upon presentation of a significant stimulus). A combination of several detection methods wa...
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The paper evaluate the row-column P300-based spelling interface for geometric modeling tasks in the engineering design process. In the first part of the paper is presented a BCI-CAD interface that can be used for geometric modeling applications. The proposed solution for BCI-CAD integration tries to preserve all advantages of using the existing legacy CAD software and add on top of it a BCI int...
متن کاملAn efficient P300-based brain-computer interface for disabled subjects.
A brain-computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In other words, a BCI allows users to act on their environment by using only brain-activity, without using peripheral nerves and muscles. In this paper, we present a BCI that achieves high classification accuracy and high bitrates for both disabled and able-bo...
متن کاملA Study of Various Feature Extraction Methods on a Motor Imagery Based Brain Computer Interface System
Introduction: Brain Computer Interface (BCI) systems based on Movement Imagination (MI) are widely used in recent decades. Separate feature extraction methods are employed in the MI data sets and classified in Virtual Reality (VR) environments for real-time applications. Methods: This study applied wide variety of features on the recorded data using Linear Discriminant Analysis (LDA) classifie...
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ژورنال
عنوان ژورنال: Journal of Medical Imaging and Health Informatics
سال: 2014
ISSN: 2156-7018,2156-7026
DOI: 10.1166/jmihi.2014.1267